Abstract

A CPS is a Cyber-Physical System in which computers control things that happen in the real world, making it easier to monitor and automate factories and other workplaces. The CPS plays a vital role in ensuring that everything functions well, accurately, and in real time within smart grids, energy systems, and manufacturing sectors. With increased connectivity and integration of these CPSs, hackers have been highly likely to attack such systems to gain unauthorized access and disrupt operations. When the network is slow, there are data errors, and hardware fails, it's still a big problem to keep the system running. This paper investigates the state of the art with respect to the principal concerns of security and dependability in Cyber-Physical Systems for factory automation. Advanced tools employed include AI-driven enhancements toward effective problem identification and prediction, intrusion detection systems, fault-tolerant control, and real-time monitoring. Fault-tolerant systems ensure continuity in the operation of systems even in adverse conditions of hardware or network failure. Real-time intrusion detection systems secure operations by preventing possible cyber threats before occurrence. AI-driven prediction models enhance system operability by detecting problems well in advance and undertaking necessary steps to mitigate related operational risks before their occurrence. Landmark studies underpin that CPS is significantly more stable when strong security frameworks are employed along with efficient fault management systems. AI-driven controls enhance the efficiency of systems by keeping them operable through reduced downtime, reduce their hackability, and ensure continuity of operations. This paper addresses strategies to enhance and secure the CPS of industrial automation to cater to and fulfill the ever-evolving requirements of contemporary enterprises.

Keywords

Cyber-Physical Systems, Industrial Automation, Security, Reliability, Intrusion Detection, Fault-Tolerant Systems, AI-Based Control.

Conclusion

In short, most factories in these modern days involve the utilization of Cyber-Physical Systems. These systems make things better, more accurate, and all this in real time. However, as computers take charge of more physical processes, security and reliability issues are likely to become more probable. This study depicts some of the challenges involved in ensuring safety and dependability in Cyber-Physical Systems, particularly within industrial settings. This study proves that an approach based on advanced technology integration, like IDSs in real time, FTC, and predictive models based on AI, are helpful in enhancing the safety and dependability of Cyber-Physical Systems. We shall need intrusion detection systems to find and block all types of cyber perils in real time. These prevent people who should not get in from getting in and prevent attacks. On the contrary, fault-tolerant systems keep working even in case specific problems happen at the network or hardware level. In this manner, it makes sure that the system works smoothly and seldom goes down. AI-based controls also make sure that systems work better. This research illustrates well that an integrated use of these technologies can enhance the dependability of CPS by lowering the possibility of any problem and improving its general performance. These results demonstrate that CPS in industrial automation requires a holistic approach, as the fault management and security framework must be combined in order to address the challenges that it faces. This research provides one of the significant fundamentals to increasing the resilience of such systems and hence their capability to fulfill the ever-increasing demands of modern-day industrial settings as industries progress and integrate CPS technologies.

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